Exabeam Fusion vs. Logstash

As a SIEM tool for investigations, Exabeam is the best in class. The AI assigns numeric values to observed logs them presents high scores to the analyst in a simple dashboard. We can see what is a real threat and ignore so many false positives. Exabeam is the best SIEM was used from an alert fatigue perspective. The simple interface allows other teams not just InfoSec to utilize the tool; helpdesk for asset diagnoses, HR for staffing questions, etc.

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Perfect for projects where Elasticsearch makes sense: if you decide to employ ES in a project, then you will almost inevitably use LogStash, and you should anyways. Such projects would include: 1. Data Science (reading, recording or measure web-based Analytics, Metrics) 2. Web Scraping (which was one of our earlier projects involving LogStash) 3. Syslog-ng Management: While I did point out that it can be a bit of an electric boo-ga-loo in finding an errant configuration item, it is still worth it to implement Syslog-ng management via LogStash: being able to fine-tune your log messages and then pipe them to other sources, depending on the data being read in, is incredibly powerful, and I would say is exemplar of what modern Computer Science looks like: Less Specialization in mathematics, and more specialization in storing and recording data (i.e. Less Engineering, and more Design).

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• Fast search times, unlike other competing solutions.
• The ability for engineers to obtain access to the command line interface for troubleshooting, at least for on-premise deployments.
• License is suitable for organisations with lots of logs to ingest.
• Hardware required for on premise deployments is well supported.

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• Logstash design is definitely perfect for the use case of ELK. Logstash has "drivers" using which it can inject from virtually any source. This takes the headache from source to implement those "drivers" to store data to ES.
• Logstash is fast, very fast. As per my observance, you don't need more than 1 or 2 servers for even big size projects.
• Data in different shape, size, and formats? No worries, Logstash can handle it. It lets you write simple rules to programmatically take decisions real-time on data.
• You can change your data on the fly! This is the CORE power of Logstash. The concept is similar to Kafka streams, the difference being the source and destination are application and ES respectively.

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• More and better drop-down menus, some items in threat hunter require you know subsets.
• Less dashboards, combine AA and DL without having separate logins.
• More complete playbooks are already built out. You have the structure set up for templates like malware and phishing, go further and completely build them out from start to finish, most companies would just use them and not personalize their configurations.
• Quarterly health checkup diagnostics of systems sent out to users.

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• It is heavy i.e., intensive as of now. Need to reduce overhead to save CPU/RAM consumption
• Need to be more Kubernetes-friendly. Should support auto-scaling and K8s observability
• Initial configuration is still complex. A seamless config procedure is still required

Exabeam is very good at processing lots of logs without excessive licensing costs. It has a professional support team that's very quick to resolve any issues and provides custom parsers quickly and enables our analysts to search vast data sets without having to wait long for results to be returned. The product is getting more mature with new features every major release.

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As I said earlier, for a production-grade OpenStack Telco cloud, Logstash brings high value in flexibility, compliance, and troubleshooting efficiency. However, this brings a higher infra & ops cost on resources, but that is not a problem in big datacenters because there is no resource crunch in terms of servers or CPU/RAM

Exabeam Fusion has so many diffferent out reach meetings, webinars, community virtual coffees, and events that you can always stay abreast of what if happening and get new ideas for use cases. Their support actually answers their phones and can respond in chat instantly. With our cloud deployment Exabeam support teams can instantly see our systems and help us.

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Logstash can be compared to other ETL frameworks or tools, but it is also complementary to several, for example, Kafka. I would not only suggest using Logstash when the rest of the ELK stack is available, but also for a self-hosted event collection pipeline for various searching systems such as Solr or Graylog, or even monitoring solutions built on top of Graphite or OpenTSDB.

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• Reduced time to triage alerts.
• Reduced number of alerts which need escalation to senior tiers.
• The ability for analysts to quickly run playbooks for additional information and enrichment.
• Ability to retain data for longer periods for forensics purposes.
• Improved search performance compared with other SIEM solutions.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Positive: LogStash is OpenSource. While this should not be directly construed as Free, it's a great start towards Free. OpenSource means that while it's free to download, there are no regular patch schedules, no support from a company, no engineer you can get on the phone / email to solve a problem. You are your own Engineer. You are your own Phone Call. You are your own ticketing system.
• Negative: Since Logstash's features are so extensive, you will often find yourself saying "I can just solve this problem better going further down / up the Stack!". This is not a BAD quality, necessarily and it really only depends on what Your Project's Aim is.
• Positive: LogStash is a dream to configure and run. A few hours of work, and you are on your way to collecting and shipping logs to their required addresses!

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info